Dynamic range of hypercubic stochastic excitable media
arXiv:0707.0309 · doi:10.1103/PhysRevE.77.011923
Abstract
We study the response properties of d-dimensional hypercubic excitable networks to a stochastic stimulus. Each site, modelled either by a three-state stochastic susceptible-infected-recovered-susceptible system or by the probabilistic Greenberg-Hastings cellular automaton, is continuously and independently stimulated by an external Poisson rate h. The response function (mean density of active sites rho versus h) is obtained via simulations (for d=1, 2, 3, 4) and mean field approximations at the single-site and pair levels (for all d). In any dimension, the dynamic range of the response function is maximized precisely at the nonequilibrium phase transition to self-sustained activity, in agreement with a reasoning recently proposed. Moreover, the maximum dynamic range attained at a given dimension d is a decreasing function of d.
7 pages, 4 figures
References in corpus (8)
- Scale-free brain functional networks
- Optimal Dynamical Range of Excitable Networks at Criticality
- Critical brain networks
- Physics of Psychophysics: Stevens and Weber-Fechner laws are transfer functions of excitable media
- Pair approximation of the stochastic susceptible-infected-recovered-susceptible epidemic model on the hypercubic lattice
- Response of electrically coupled spiking neurons: a cellular automaton approach
- Excitable Scale Free Networks
- Intensity Coding in Two-Dimensional Excitable Neural Networks
Cited by in corpus (18)
- Criticality in the brain: A synthesis of neurobiology, models and cognition
- Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle
- Active dendrites enhance neuronal dynamic range
- Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus
- Single-Neuron Criticality Optimizes Analog Dendritic Computation
- Statistical Physics approach to dendritic computation: The excitable-wave mean-field approximation
- Signal integration enhances the dynamic range in neuronal systems
- Diversity improves performance in excitable networks
- Deterministic excitable media under Poisson drive: power law responses, spiral waves and dynamic range
- Discontinuous nonequilibrium phase transitions in a nonlinearly pulse-coupled excitable lattice model
- Scaling behaviour in probabilistic neuronal cellular automata
- Collective oscillations of excitable elements: order parameters, bistability and the role of stochasticity
- Physics of Psychophysics: two coupled square lattices of spiking neurons have huge dynamic range at criticality
- An excitable electronic circuit as a sensory neuron model
- Mechanisms of self-organized quasicriticality in neuronal networks models
- Critical Network Cascades with Re-excitable nodes: Why tree-like approximations usually work, when they breakdown, and how to correct them
- Coloring Fibonacci-Cayley tree: An application to neural networks
- Interplay between Network Topology and Dynamics in Neural Systems